Opportunity ID: 359326

General Information

Document Type: Grants Notice
Funding Opportunity Number: PD-13-7607
Funding Opportunity Title: Energy, Power, Control and Networks
Opportunity Category: Discretionary
Opportunity Category Explanation:
Funding Instrument Type: Grant
Category of Funding Activity: Science and Technology and other Research and Development
Category Explanation:
Expected Number of Awards:
Assistance Listings: 47.041 — Engineering
Cost Sharing or Matching Requirement: No
Version: Synopsis 1
Posted Date: Jun 06, 2025
Last Updated Date: Jun 06, 2025
Original Closing Date for Applications: – Opportunity is Archived
Current Closing Date for Applications: – Opportunity is Archived
Archive Date: Jun 07, 2025
Estimated Total Program Funding:
Award Ceiling:
Award Floor:

Eligibility

Eligible Applicants: Unrestricted (i.e., open to any type of entity above), subject to any clarification in text field entitled “Additional Information on Eligibility”
Additional Information on Eligibility:

Additional Information

Agency Name: U.S. National Science Foundation
Description: Recent advances in communications, computation, and sensing technologies offer unprecedented opportunities for the design of cyber-physical systems with increased responsiveness, interconnectivity and automation. To meet new challenges and societal needs, the Energy, Power, Control andNetworks (EPCN) Program invests in systems and control methods for analysis and design of cyber-physical systems to ensure stability, performance, robustness, and security. Topics of interest include modeling, optimization, learning, and control of networked multi-agent systems, higher-level decision making, and dynamic resource allocation as well as risk management in the presence of uncertainty, sub-system failures and stochastic disturbances. EPCN also invests in adaptive dynamic programing, brain-like networked architectures performing real-time learning, and neuromorphic engineering. EPCN supports innovative proposals dealing with systems research in such areas as energy, transportation, and nanotechnology. EPCN places emphasis on electric power systems, including generation, transmission, storage, and integration of renewables; power electronics and drives; battery management systems; hybrid and electric vehicles; and understanding of the interplay of power systems with associated regulatory and economic structures and with consumer behavior. Also of interest are interdependencies of power and energy systems with other critical infrastructures. Topics of interest include energy scavenging and alternate energy technologies such as solar, wind, and hydrokinetic. The program also supports innovative tools and test beds, as well as curriculum development integrating research and education. In addition to single investigator projects, EPCN encourages cross-disciplinary proposals that benefit from active collaboration of researchers with complementary skills.

Proposals for the EPCN program may involve collaborative research to capture the breadth of expertise needed for such multidisciplinary integrative activities. ECCS will consider supporting a limited number of small team proposals of three or more Investigators from different disciplines and/or universities.

Areas covered by the EPCN Group (Abed, Baheti, and Werbos):

  • Control Theory and Hybrid Dynamical Systems
  • Networked Multi-agent Systems
  • Cyber Physical Systems Modeling and Control
  • System Theory for Biology and Medicine; Modeling of the Brain
  • Control and Optimization in Buildings, Transportation, and Robotics
  • Adaptive and Intelligent Systems; Neural Networks
  • Energy Harvesting, Storage Devices and Systems
  • Solar and Wind Energy and Integration of Renewables with Grid
  • Monitoring, Protection and Cyber Security of Power Grid
  • Advanced Power Electronics and Electric Machines
  • Electric and Hybrid Vehicles; Integration with Grid
  • Policy, Economics, Consumer Behavior and the Power Grid
  • Quantum, Molecular and High Performance Modeling and Simulation for Devices and Systems (QMHP) (Paul Werbos)
Link to Additional Information: NSF Program Desccription PD-13-7607
Grantor Contact Information: If you have difficulty accessing the full announcement electronically, please contact:

NSF grants.gov support
grantsgovsupport@nsf.gov
Email:grantsgovsupport@nsf.gov

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2025-07-14T06:56:21-05:00

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